» Articles » PMID: 37255610

Predictors of Beverage-specific, Alcohol Consumption Trajectories: A Swedish Population-based Cohort Study

Overview
Specialty Psychiatry
Date 2023 May 31
PMID 37255610
Authors
Affiliations
Soon will be listed here.
Abstract

The aim of the study was to examine whether changes in alcohol consumption over time differ according to beverage types, and to what extent socioeconomic, lifestyle and health-related factors predict beverage-specific trajectories in Sweden. We included participants from the Stockholm Public Health Cohort who were surveyed repeatedly in 2002, 2010 and 2014. Alcohol consumption trajectories were constructed for 13,152 individuals with valid information on amount and frequency of drinking. Preferred beverage types (i.e., beer, wine or spirits) were defined based on the most consumed beverages. Multinomial logistic regression was used to quantify individual predictors of different trajectories, overall and by beverage type. Overall 56.9% of respondents were women, the mean age was 49.2 years, SD (13.1). Wine was cited as the preferred beverage for 72.4% of participants, and stable moderate drinking was the most common trajectory regardless of beverage type (68.2%, 54.9% and 54.2% in individuals with wine, beer and spirits as preferred beverages, respectively). Associations between drinking trajectories and baseline lifestyle factors did not differ by beverage type. Lower socioeconomic position (SEP) was associated with unstable moderate wine drinking (for unskilled manual SEP: adjusted odds ratio [aOR] 1.54, 95% confidence interval [CI] 1.23, 1.93), unstable heavy beer drinking (for skilled manual SEP: aOR 1.99, 95% CI 1.14, 3.52; and unskilled manual SEP: aOR 1.72, 95% CI 1.05, 2.82), and former beer drinking trajectory (for skilled manual SEP: aOR 1.81; 95% CI 1.21, 2.72; and unskilled manual SEP: aOR 1.66; 95% CI 1.17, 2.37). Lower SEP was associated with unstable heavy drinking of beer, former beer drinking, and unstable moderate wine drinking trajectories indicating that targeted alcohol prevention programmes need to focus on these groups.

Citing Articles

Alcohol consumption trajectories and associated factors in adult women: the Norwegian Women and Cancer study.

Llaha F, Licaj I, Sharashova E, Borch K, Lukic M Alcohol Alcohol. 2025; 60(2).

PMID: 39921373 PMC: 11806201. DOI: 10.1093/alcalc/agaf005.


The alcohol harm paradox: is it valid for self-reported alcohol harms and does hazardous drinking pattern matter?.

Rossow I, Bye E BMC Public Health. 2024; 24(1):3053.

PMID: 39501200 PMC: 11539690. DOI: 10.1186/s12889-024-20530-9.


Our content is relevant and on track.

Kettunen T Nordisk Alkohol Nark. 2023; 40(3):215-217.

PMID: 37255605 PMC: 10225961. DOI: 10.1177/14550725231175570.

References
1.
Dey M, Gmel G, Studer J, Dermota P, Mohler-Kuo M . Beverage preferences and associated drinking patterns, consequences and other substance use behaviours. Eur J Public Health. 2013; 24(3):496-501. DOI: 10.1093/eurpub/ckt109. View

2.
Andreasson S, Allebeck P, Romelsjo A . Alcohol and mortality among young men: longitudinal study of Swedish conscripts. Br Med J (Clin Res Ed). 1988; 296(6628):1021-5. PMC: 2545555. DOI: 10.1136/bmj.296.6628.1021. View

3.
Berg N, Kiviruusu O, Karvonen S, Kestila L, Lintonen T, Rahkonen O . A 26-year follow-up study of heavy drinking trajectories from adolescence to mid-adulthood and adult disadvantage. Alcohol Alcohol. 2013; 48(4):452-7. DOI: 10.1093/alcalc/agt026. View

4.
Knott C, Bell S, Britton A . The stability of baseline-defined categories of alcohol consumption during the adult life-course: a 28-year prospective cohort study. Addiction. 2017; 113(1):34-43. PMC: 5725237. DOI: 10.1111/add.13949. View

5.
Moore A, Gould R, Reuben D, Greendale G, Carter M, Zhou K . Longitudinal patterns and predictors of alcohol consumption in the United States. Am J Public Health. 2005; 95(3):458-65. PMC: 1449202. DOI: 10.2105/AJPH.2003.019471. View